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Examining the State and Market Forces Behind Information Control in China

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Examining the State and Market Forces Behind Information Control in China Delegated Dictatorship: Examining the State and Market Forces behind Information Control in China by Blake Miller A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Political Science and Scientific Computing) in The University of Michigan 2018 Doctoral Committee: Professor Mary Gallagher, Chair Professor Pauline Jones Professor Walter Mebane Professor Nicholas Valentino Blake Miller [email protected] ORCID iD: 0000-0002-4707-0984 c Blake Miller 2018 All Rights Reserved ACKNOWLEDGEMENTS The seed of this dissertation was planted in 2008 when I was fortunate enough to meet Larry Diamond and to take the excellent Chinese Politics class taught by Alice Miller as an undergraduate at Stanford University. I spent the next 3 years as Larry's research assistant, studying internet censorship in China, and became fascinated by the online conflict between state and society that seemed to be pushing China in a more open, liberal, and democratic direction. Larry encouraged me to go to China and conduct fieldwork for an undergraduate thesis on the use of the internet to control dissent. Semi-structured interviews with the signers and drafters of Charter 08 opened my eyes to the real-world consequences of online dissent in authoritarian regimes. This experience provided a strong foundation upon which I built my graduate school research agenda. I am incredibly grateful to Alice Miller and Larry Diamond for their support and encouragement at this early stage. Going through graduate school and writing a dissertation is an extraordinarily difficult and stressful process. I was very fortunate to have many kind, thoughtful, and supporting friends, family members, mentors, and research assistants who made the process easier, and an incredibly meaningful and rewarding experience. Thanks to my parents, Blake and Jeryl Miller for your encouragement and support throughout grad school. Thanks as well to my brother Luke Miller and his partner Lisa Quadt, two grad school veterans who are always supportive and thoughtful. To the friends and fellow graduate students I met on my first day at Michi- gan, Sasha de Vogel, Zander Furnas, Joseph Klaver, Steven Moore, and Michael ii Thompson-Brusstar, thanks for being the most amazing group of friends throughout the entirety of my time at Michigan. You were always supportive when I doubted my work, always listened to me when I was feeling discouraged, and always made sure that I took breaks when I needed them. To Nicole Wu, thanks for being a great friend throughout my time at Michigan, for sending me ALL the cute dog pictures, and for double-checking my attempts to translate Mandarin into English. Thanks to all of the other friends and acquaintances in Ann Arbor who made grad school a pleasant and memorable experience. Thanks to my dissertation committee Mary Gallagher, Walter Mebane, Pauline Jones, and Nicholas Valentino for their incredible feedback, generosity, and thought- fulness. Mary, thanks for your honest and frank feedback in our many meetings together, for helping me focus and expand my research agenda when necessary, for fostering a community of grad students studying China, and for taking the time to introduce me to scholars outside of Michigan who have mentored me throughout my time at Michigan. Walter, thank you for encouraging me in my interest in machine learning and natural language processing early on in grad school, for your generosity with time and resources, and for allowing me to use your personal server for data col- lection, even when it slowed your own work down (sorry about that again). Pauline, thanks for keeping me honest when it came to theory development and for pushing me to be more systematic in my research process. Thank you Nick for helping me with the design of my survey experiments, and for telling me not to worry when I was unnecessarily concerned about outcomes of grants, funding, and the job market. Thank you to Daniela Stockmann, who hosted me multiple times in Berlin and in Shanghai, and who has become an incredible mentor and friend. Thanks to Yuhua Wang, Iza Ding, and Jeffrey Javed for mentorship and feedback during grad school that undoubtedly has made me a better scholar, and has improved the quality of my work. iii Thanks to Yuen Yuen Ang, Christian Davenport, Chris Fariss, Allen Hicken, Brian Min, James Morrow, Ragnhild Nordas, Iain Osgood, and Charles Shipan for their feedback at workshops and meetings at the University of Michigan. Thank you to Margaret Roberts, Haifeng Huang, Pierre Landry, and Bruce Dickson for your feedback on my work. This dissertation would not have been possible without the excellent research assistantship of Emma, Leon, Shannon, Qiwei, Moira, Zhang, Martin, Chen, Erin, Yingsi, Jack, Ziyi, and Sherry. Thanks for your dedication and hard work that has resulted in the datasets used in this dissertation. Thanks to Sweetland Writing Center at the University of Michigan for arranging dissertation writing groups and providing excellent writing help. Thanks to Simone Sessolo for reading many drafts of my chapters. Thanks to my dissertation writing group members Angie Baecker, Chinbo Chong, and Nicole Hentrich for workshop- ping my writing. Thanks as well to The University of Michigan's Asia Library and particularly the help of Liangyu Fu who helped me obtain many of the fascinating government documents and manuals that informed my research. Thanks to the amazing group of researchers at The Citizen Lab at University of Toronto for helping me with my work and inspiring me with all of their amazing re- search. Thanks especially to Masashi Crete-Nishihata, Ron Diebert, Jeffrey Knockel, and Lotus Ruan for reading and commenting on early drafts of chapters. iv TABLE OF CONTENTS ACKNOWLEDGEMENTS :::::::::::::::::::::::::: ii LIST OF FIGURES ::::::::::::::::::::::::::::::: viii LIST OF TABLES :::::::::::::::::::::::::::::::: ix ABSTRACT ::::::::::::::::::::::::::::::::::: x CHAPTER I. Introduction: Delegation and Covert Censorship in China .1 1.1 The Puzzle of Imperfect Information Control In China....3 1.2 Maximalist Censorship Strategy and Covert Implementation.6 1.3 A Brief History of Information Control In China.......9 1.3.1 Pre-Internet Information Controls..........9 1.3.2 Post-Internet Information Controls.......... 12 1.4 How Corporate-Delegated Censorship Works......... 15 1.5 Data................................ 16 1.5.1 Leaked Censorship Logs................ 17 1.5.2 Measures of Censorship (Free Weibo and Weiboscope) 20 1.6 Roadmap............................. 20 II. Covert Censorship ........................... 24 2.1 Introduction........................... 24 2.2 Background............................ 25 2.2.1 Types of Censorship.................. 25 2.2.2 Types of Censorship at Sina Weibo......... 27 2.3 Covert Censorship........................ 29 2.4 The Market Logic of Covert Censorship............ 30 2.5 Empirical Analysis........................ 32 2.6 Discussion............................ 34 2.7 Conclusion............................ 36 v III. The Limits of Commercialized Censorship in China ...... 37 3.1 The Southern Weekend Incident................ 38 3.2 Delegation, Fragmentation, and Agency Loss......... 40 3.2.1 Corporate Delegation Leads to Agency Loss.... 41 3.2.2 Bureaucratic Fragmentation Leads to Agency Loss. 43 3.3 Data and Methods........................ 45 3.3.1 Log Data........................ 46 3.3.2 Event Data....................... 47 3.3.3 Censorship Outcomes Data.............. 48 3.4 Empirical Implications and Results............... 49 3.4.1 Corporate Delegation Leads to Agency Loss.... 50 3.4.2 Bureaucratic Fragmentation Leads to Agency Loss. 53 3.5 Conclusion............................ 58 3.6 Developments Since 2014.................... 59 3.7 Beyond China.......................... 60 IV. Reassessing the Targets of China's Online Censorship Appa- ratus ................................... 64 4.1 Introduction........................... 65 4.2 Collective Action Potential vs. Low Censorship Capacity... 66 4.3 Data and Methods........................ 67 4.3.1 Leaked Log Data................... 67 4.3.2 Coding Procedure................... 69 4.3.3 Empirical Expectations................ 72 4.4 Results.............................. 73 4.5 Discussion............................ 75 4.5.1 Beyond Collective Action Potential......... 76 4.5.2 Why Government Intent Should Not be Inferred from Censorship Outcomes................. 77 4.6 Conclusion............................ 79 V. Automated Detection of Chinese Government Astroturfers Using Network and Social Metadata ............... 80 5.1 Introduction........................... 80 5.2 Identifying Government Astroturfers.............. 84 5.2.1 What We Know About Government Astroturfers.. 84 5.2.2 Labeling Observations................. 87 5.2.3 What are the Defining Attributes of Government As- troturfer Behavior?.................. 88 5.2.4 Rules for Automatically Labeling Comments.... 88 5.3 Government Weibo Account Classifier............. 93 vi 5.3.1 Features........................ 94 5.3.2 Labeling Government Accounts........... 95 5.3.3 Performance of Government Weibo Classifier.... 96 5.3.4 Network Structure and Inferring the Bureaucratic Affiliation of Astroturfers............... 97 5.4 Government Astroturfer Classifier............... 98 5.4.1 Text Features..................... 99 5.4.2 Performance of Classifiers............... 100 5.4.3 Estimated Percent of Government Astroturfers in News Comment Sections..................
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